Literature DB >> 12405365

Histopathological validation of a three-dimensional magnetic resonance spectroscopy index as a predictor of tumor presence.

Tracy R McKnight1, Mary H von dem Bussche, Daniel B Vigneron, Ying Lu, Mitchel S Berger, Michael W McDermott, William P Dillon, Edward E Graves, Andrea Pirzkall, Sarah J Nelson.   

Abstract

OBJECT: Data obtained preoperatively from three-dimensional (3D)/proton magnetic resonance (MR) spectroscopy were compared with the results of histopathological assays of tissue biopsies obtained during surgery to verify the sensitivity and specificity of a choline-containing compound-N-acetylaspartate index (CNI) used to distinguish tumor from nontumorous tissue within T2-hyperintense and contrast-enhancing lesions of patients with untreated gliomas. The information gleaned from the biopsy correlation study was used to test the hypothesis that there is metabolically active tumor in nonenhancing regions of the T2-hyperintense lesion that can be detected using MR spectroscopy.
METHODS: Patients suspected of harboring a glioma underwent 3D MR spectroscopy during their preoperative MR imaging examination. Surgical navigation techniques were used to record the location of tissue biopsies collected during open resection of the tumor. A receiver operating curve analysis of the CNI and histological characteristics of specimens at each biopsy location was performed to determine the optimal threshold of the CNI required to separate tumor from nontumorous tissue. Histograms of the CNIs within enhancing and nonenhancing regions of lesions appearing on MR images were generated to determine the spatial distribution of CNIs consistent with tumor.
CONCLUSIONS: Biopsy samples containing tumor were distinguished from those containing a mixture of normal, edematous, gliotic, and necrotic tissue with 90% sensitivity and 86% specificity by using a CNI threshold of 2.5. The CNIs of nontumorous specimens were significantly different from those of biopsy specimens containing Grade II (p < 0.03), Grade III (p < 0.005), and Grade IV (p < 0.01) tumors. On average, one third to one half of the T2-hyperintense lesion outside the contrast-enhancing lesion contained CNI greater than 2.5.

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Year:  2002        PMID: 12405365     DOI: 10.3171/jns.2002.97.4.0794

Source DB:  PubMed          Journal:  J Neurosurg        ISSN: 0022-3085            Impact factor:   5.115


  74 in total

1.  Ex vivo MR spectroscopic measure differentiates tumor from treatment effects in GBM.

Authors:  Radhika Srinivasan; Joanna J Phillips; Scott R Vandenberg; Mei-Yin C Polley; Gabriela Bourne; Alvin Au; Andrea Pirzkall; Soonmee Cha; Susan M Chang; Sarah J Nelson
Journal:  Neuro Oncol       Date:  2010-07-20       Impact factor: 12.300

2.  Clinical target volume delineation in glioblastomas: pre-operative versus post-operative/pre-radiotherapy MRI.

Authors:  P Farace; M G Giri; G Meliadò; D Amelio; L Widesott; G K Ricciardi; S Dall'Oglio; A Rizzotti; A Sbarbati; A Beltramello; S Maluta; M Amichetti
Journal:  Br J Radiol       Date:  2010-11-02       Impact factor: 3.039

3.  The relationship between Cho/NAA and glioma metabolism: implementation for margin delineation of cerebral gliomas.

Authors:  Jun Guo; Chengjun Yao; Hong Chen; Dongxiao Zhuang; Weijun Tang; Guang Ren; Yin Wang; Jinsong Wu; Fengping Huang; Liangfu Zhou
Journal:  Acta Neurochir (Wien)       Date:  2012-06-23       Impact factor: 2.216

4.  Assessment of perfusion MRI-derived parameters in evaluating and predicting response to antiangiogenic therapy in patients with newly diagnosed glioblastoma.

Authors:  Emma Essock-Burns; Janine M Lupo; Soonmee Cha; Mei-Yin Polley; Nicholas A Butowski; Susan M Chang; Sarah J Nelson
Journal:  Neuro Oncol       Date:  2010-10-29       Impact factor: 12.300

Review 5.  A systematic literature review of magnetic resonance spectroscopy for the characterization of brain tumors.

Authors:  W Hollingworth; L S Medina; R E Lenkinski; D K Shibata; B Bernal; D Zurakowski; B Comstock; J G Jarvik
Journal:  AJNR Am J Neuroradiol       Date:  2006-08       Impact factor: 3.825

6.  Patterns of recurrence analysis in newly diagnosed glioblastoma multiforme after three-dimensional conformal radiation therapy with respect to pre-radiation therapy magnetic resonance spectroscopic findings.

Authors:  Ilwoo Park; Gregory Tamai; Michael C Lee; Cynthia F Chuang; Susan M Chang; Mitchel S Berger; Sarah J Nelson; Andrea Pirzkall
Journal:  Int J Radiat Oncol Biol Phys       Date:  2007-05-21       Impact factor: 7.038

Review 7.  New advances that enable identification of glioblastoma recurrence.

Authors:  Isaac Yang; Manish K Aghi
Journal:  Nat Rev Clin Oncol       Date:  2009-10-06       Impact factor: 66.675

8.  Identifying Voxels at Risk for Progression in Glioblastoma Based on Dosimetry, Physiologic and Metabolic MRI.

Authors:  Mekhail Anwar; Annette M Molinaro; Olivier Morin; Susan M Chang; Daphne A Haas-Kogan; Sarah J Nelson; Janine M Lupo
Journal:  Radiat Res       Date:  2017-07-19       Impact factor: 2.841

9.  Evaluation of MR markers that predict survival in patients with newly diagnosed GBM prior to adjuvant therapy.

Authors:  Suja Saraswathy; Forrest W Crawford; Kathleen R Lamborn; Andrea Pirzkall; Susan Chang; Soonmee Cha; Sarah J Nelson
Journal:  J Neurooncol       Date:  2008-09-23       Impact factor: 4.130

10.  Multiparametric characterization of grade 2 glioma subtypes using magnetic resonance spectroscopic, perfusion, and diffusion imaging.

Authors:  Wei Bian; Inas S Khayal; Janine M Lupo; Colleen McGue; Scott Vandenberg; Kathleen R Lamborn; Susan M Chang; Soonmee Cha; Sarah J Nelson
Journal:  Transl Oncol       Date:  2009-12       Impact factor: 4.243

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